| Literature DB >> 33477749 |
Ming Liang Oon1, Jing Quan Lim2,3, Bernett Lee4, Sai Mun Leong5, Gwyneth Shook-Ting Soon1, Zi Wei Wong1, Evelyn Huizi Lim6, Zhenhua Li6, Allen Eng Juh Yeoh6,7, Shangying Chen8, Kenneth Hon Kim Ban8, Tae-Hoon Chung9, Soo-Yong Tan1,5, Shih-Sung Chuang10, Seiichi Kato11,12, Shigeo Nakamura11, Emiko Takahashi13, Yong-Howe Ho14, Joseph D Khoury15, Rex K H Au-Yeung16, Chee-Leong Cheng17, Soon-Thye Lim18, Wee-Joo Chng9,19, Claudio Tripodo20, Olaf Rotzschke4, Choon Kiat Ong2,3,21, Siok-Bian Ng1,5,9.
Abstract
T-cell lymphomas arise from a single neoplastic clone and exhibit identical patterns of deletions in T-cell receptor (TCR) genes. Whole genome sequencing (WGS) data represent a treasure trove of information for the development of novel clinical applications. However, the use of WGS to identify clonal T-cell proliferations has not been systematically studied. In this study, based on WGS data, we identified monoclonal rearrangements (MRs) of T-cell receptors (TCR) genes using a novel segmentation algorithm and copy number computation. We evaluated the feasibility of this technique as a marker of T-cell clonality using T-cell lymphomas (TCL, n = 44) and extranodal NK/T-cell lymphomas (ENKTLs, n = 20), and identified 98% of TCLs with one or more TCR gene MRs, against 91% detected using PCR. TCR MRs were absent in all ENKTLs and NK cell lines. Sensitivity-wise, this platform is sufficiently competent, with MRs detected in the majority of samples with tumor content under 25% and it can also distinguish monoallelic from biallelic MRs. Understanding the copy number landscape of TCR using WGS data may engender new diagnostic applications in hematolymphoid pathology, which can be readily adapted to the analysis of B-cell receptor loci for B-cell clonality determination.Entities:
Keywords: T-cell lymphoma; T-cell receptor; clonality; copy number variation analysis; whole genome sequencing
Year: 2021 PMID: 33477749 PMCID: PMC7832336 DOI: 10.3390/cancers13020340
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639